JOURNAL OF NATURAL RESOURCES ›› 2018, Vol. 33 ›› Issue (10): 1725-1741.doi: 10.31497/zrzyxb.20170802

• Resource Ecology • Previous Articles     Next Articles

The Estimation of Forest Vegetation Biomass in China in Spatial Grid

XU Wei-yi1,2,3, JIN Xiao-bin1,3,4, YANG Xu-hong1,3, WANG Zhi-qiang2, LIU Jing1,3, WANG Dan5, SHAN Wei1, ZHOU Yin-kang1,3,4   

  1. 1. School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210023, China;
    2. School of Resource Environment and Safety Engineering, Hunan University of Science and Technology, Xiangtan 411100, China;
    3. The Key Laboratory of the Coastal Zone Exploitation and Protection, Ministry of Land and Resources, Nanjing 210023, China;
    4. Natural Resources Research Center, Nanjing University, Nanjing 210023, China;
    5. School of Geography Geomatics and Planning, Jiangsu Normal University, Xuzhou 221116, China
  • Received:2017-08-07 Revised:2017-12-25 Online:2018-10-20 Published:2018-10-20
  • Supported by:
    National Natural Science Foundation of China, No. 41671082.

Abstract: Forest is a major carbon pool for terrestrial ecosystems, and it plays a very important role in global carbon cycle. Forest biomass is a key factor in estimating forest carbon storage, and its magnitude and spatial distribution are important parameters for assessing carbon sequestration potential of forest ecosystems. Scholars in the field have used different methods to study many aspects of forest biomass in China. Due to the spatial heterogeneity of forest biomass and differences in research methods and data, different scholars got different results. Three traditional methods have been used in biomass research: on-the-spot sampling, model method and remote sensing. Currently, statistical downscaling technique is a statistical method widely used in the study of ecosystem carbon cycle which transforms large-scale, low-resolution information into regional-scale, high-resolution information. This paper is based on the eighth China forest inventory data set, along with the impact factors of forest biomass, including the vegetation factor (NDVI), climatic factors (temperature, precipitation), and terrain factors (elevation, slope). We quantitatively estimate the forest biomass (1 km resolution) using the spatial downscaling technique, and the results of the study are verified on multiple scales. The results of this study are as follows: 1) The total stock of forest biomass is 13.56 Pg in China, with an average biomass of 65.3 t/hm2. The total amount of forest biomass is quite different in different provinces. The provinces with higher volume are concentrated in the southwest and the northeast, and the maximum biomass is 4.5 Pg in the southwest, accounting for 33% of the total biomass in China. The forest biomass is 3.58 Pg in the northeast, accounting for 26% of the total biomass in China. 2) The regression relationship between forest biomass and related factors at the provincial scale can be used for the estimation of forest biomass at the grid scale by downscaling technique, and the multi-scale verification analysis shows that the estimation results are reasonable. 3) The spatial pattern of forest biomass is consistent with the spatial distribution of hydrothermal condition. Taking the line from the northeast to the southwest as the boundary, China’s biomass is primarily in the Da Xing’an Mountains, Xiao Xing’an Mountains and Changbai Mountain in the Northeast China, the Hengduan Mountains in the Southwest China, the Qinling Mountains, and the Wuyi Mountains in the Southeast China.

Key words: biomass, China, downscaling, forest, spatial grid

CLC Number: 

  • S718.5